Improved multilayer perceptron design by weighted learning

IEEE International Symposium on Industrial Electronics

Volumn , Issue , 2007, Pages 3424-3429

  Andina, Diego ^a   Jevtić, Aleksandar ^a  

^a UNIVERSIDAD POLITÉCNICA DE MADRID   (Spain)

Author keywords

Backpropagation training algorithm; Binary detection; Neural networks

Indexed keywords

BACKPROPAGATION; BACKPROPAGATION ALGORITHMS; ELECTRIC LOADS; ELECTRONICS INDUSTRY; IMAGE CLASSIFICATION; INDUSTRIAL ELECTRONICS; LEARNING ALGORITHMS; MEAN SQUARE ERROR; MULTILAYERS; TECHNICAL PRESENTATIONS;

ARTIFICIAL NEURAL NETWORK; BACKPROPAGATION TRAINING ALGORITHM; BINARY DETECTION; INTERNATIONAL SYMPOSIUM; LEARNING PHASE; MODIFIED BACKPROPAGATION; MULTI-LAYER PERCEPTRON; OBJECTIVE FUNCTION; TRAINING EFFICIENCY; TRAINING PATTERNS; WEIGHTING FUNCTIONS;

NEURAL NETWORKS;

EID: 50049100341     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ISIE.2007.4375167     Document Type: Conference Paper

References (7)

1. Andina D, Martínez-Antorrena J, Melgar I. "Importance Sampling in Neural Detector Training Phase", Computing with Industrial Applications, TSI Press Series on Intelligent Automation and Soft Computing Vol. 17, Albuquerque NM, USA September 2004, 500 págs. ISBN: 1-889335-23-1. IEEE Catalog No. 04EX832C.Proc.
2. Hu, Y.H., Hwang, J.N. "Introduction to Neural Networks for Signal Processing" Handbook of Neural Network Signal Processing, CRC press, Boca Ratón, FL, USA, 2002, pp. 12-41.
3. Andina D, Torres-Alegre S, Vega-Corona A, Álvarez-Vellisco A. "Advances in Neyman-Pearson Neural Detectors Design" in Lecture Notes in Computer Science, Núm. 2686, Editors: J. Mirá, J.R. Álvarez, Springer-Verlag, Berlin-Heidelberg, 2003, pp. II-249-256.
4. Andina D, Ballesteros F (eds). Recent Advances in Neural Networks. Ed. International Institute of Informatics and Systemics, IIIS press, Illinois, 260 pp. USA, 2000. ISBN 980-07-7261-8.
5. Marcum J. "A statistical theory of target detection by pulsed radar", IEEE Transactions on Information Theory, Vol. 6, Issue 2, pp: 59-267, April 1960.
6. RumelHart, Hinton, G.E. & Williams, R.J. "Learning representations by back-propagating errors" Nature, 323, 533 -536, 1986.
7. Phansalkar, V.V. & Sastry, P.S. "Analysis of the back-propagation algorithm with momentum". IEEE Trans. On Neural Networks, vol. 5, No 3, pp 505-506, May 1994.